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Background/objectives: Quantile-dependent expressivity occurs when a gene's phenotypic expression depends upon whether the trait (e.g., BMI) is high or low relative to its distribution. We have previously shown that the obesity effects of a genetic risk score (GRS BMI ) increased significantly with increasing quantiles of BMI. However, BMI is an inexact adiposity measure and GRS BMI explains <3% of the BMI variance. The purpose of this paper is to test BMI for quantile-dependent expressivity using a more inclusive genetic measure (h 2 , heritability in the narrow sense), extend the result to other adiposity measures, and demonstrate its consistency with purported gene-environment interactions., Subjects/methods: Quantile-specific offspring-parent regression slopes (β OP ) were obtained from quantile regression for height (ht) and computed tomography (CT), dual-energy x-ray absorptiometry (DXA), anthropometric, and bioelectrical impedance (BIA) adiposity measures. Heritability was estimated by 2β OP /(1 + r spouse ) in 6227 offspring-parent pairs from the Framingham Heart Study, where r spouse is the spouse correlation., Results: Compared to h 2 at the 10th percentile, genetic heritability was significantly greater at the 90th population percentile for BMI (3.14-fold greater, P < 10 -15 ), waist girth/ht (3.27-fold, P < 10 -15 ), hip girth/ht (3.12-fold, P = 6.3 × 10 -14 ), waist-to-hip ratio (1.75-fold, P = 0.01), sagittal diameter/ht (3.89-fold, P = 3.7 × 10 -7 ), DXA total fat/ht 2 (3.62-fold, P = 0.0002), DXA leg fat/ht 2 (3.29-fold, P = 2.0 × 10 -11 ), DXA arm fat/ht 2 (4.02-fold, P = 0.001), CT-visceral fat/ht 2 (3.03-fold, P = 0.002), and CT-subcutaneous fat/ht 2 (3.54-fold, P = 0.0004). External validity was suggested by the phenomenon's consistency with numerous published reports. Quantile-dependent expressivity potentially explains precision medicine markers for weight gain from overfeeding or antipsychotic medications, and the modifying effects of physical activity, sleep, diet, polycystic ovary syndrome, socioeconomic status, and depression on gene-BMI relationships., Conclusions: Genetic heritabilities of anthropometric, CT, and DXA adiposity measures increase with increasing adiposity. Some gene-environment interactions may arise from analyzing subjects by characteristics that distinguish high vs. low adiposity rather than the effects of environmental stimuli on transcriptional and epigenetic processes.

Background: Diagnosis and treatment for individuals with brain tumors during childhood involves sequelae, including abnormal weight gain. This symptom is commonly clustered with fatigue and increased risk for cardiovascular disease. Children's Oncology Group recommendations include annual surveillance of body mass index (BMI) and cardiometabolic comorbidities; however, there has been little emphasis on individualized screening early in survivorship. Purpose: The primary purpose of this paper is to describe the findings of abnormal weight gain and its correlates in a sample of young childhood brain tumor survivors during early survivorship. Design and Methods: This cross‐sectional multi‐site study included brain tumor survivors of ages 8–12 years who were less than 6 years posttreatment. Convenience sampling from two pediatric cancer centers in the southern United States was utilized. Data collected included BMI, parent report of sleep, and child report of fatigue and stress. Results: The sample (N = 21) consisted of children who had received chemotherapy, radiation treatment, and surgery for childhood brain tumor. BMI in overweight and obese categories exceeded normative samples with 38% at or above the 85th percentile. There were clinically significant relationships with fatigue, stress about weight, tumor location, cranial radiation, chemotherapy, and recurrence Practice Implications: Screening for abnormal weight gain and related factors, such as fatigue should begin early in survivorship after childhood brain tumor treatment completion with the aim of health promotion and disease prevention. Adiposity measurement techniques should be utilized in future clinical and research settings to improve assessment of cardiometabolic risk. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) risk factors in children have increased in prevalence. Dietary intake may modify risk. Data collected during a randomized trial testing the effect of a behavioral intervention on adiposity, blood pressure (BP), and left ventricular mass index (LVMI) were analyzed using multivariable regression to determine independent associations of sodium, sugar-sweetened beverage (SSB), and artificially sweetened beverage (ASB) intake with outcomes. High sodium intake (≥3.5 g) was associated with hypertensive BP (odds ratio 12.8; P =.027) in minimally adjusted models. High SSB intake (≥4 oz) was independently associated with body mass index z -score (β =.34; P =.035) and waist circumference z -score (β =.49; P =.022) in fully adjusted models. Any ASB intake was associated with LVMI in fully adjusted model (% change 38.22; P =.004). There was no effect modification between sodium and SSB on outcomes. Dietary factors explored in this study independently impacted CVD risk. Further effect measure modification should be explored in larger cohorts. [ABSTRACT FROM AUTHOR]

Summary: Background: Gestational weight gain (GWG) and anthropometric trajectories may affect foetal programming and are potentially modifiable. Objectives: To assess concomitant patterns of change in weight, circumferences and adiposity across gestation as an integrated prenatal exposure, and determine how they relate to neonatal body composition. Methods: Data are from a prospective cohort of singleton pregnancies (n = 2182) enrolled in United States perinatal centres, 2009–2013. Overall and by prepregnancy BMI group (overweight/obesity and healthy weight), joint latent trajectory models were fit with prenatal weight, mid‐upper arm circumference (MUAC), triceps (TSF) and subscapular (SSF) skinfolds. Differences in neonatal body composition by trajectory class were assessed via weighted least squares. Results: Six trajectory patterns reflecting co‐occurring changes in weight and MUAC, SSF and TSF across pregnancy were identified overall and by body mass index (BMI) group. Among people with a healthy weight BMI, some differences were observed for neonatal subcutaneous adipose tissue, and among individuals with overweight/obesity some differences in neonatal lean mass were found. Neonatal adiposity measures were higher among infants born to individuals with prepregnancy overweight/obesity. Conclusions: Six integrated trajectory patterns of prenatal weight, subcutaneous adipose tissue and circumferences were observed that were minimally associated with neonatal body composition, suggesting a stronger influence of prepregnancy BMI. [ABSTRACT FROM AUTHOR]

Background: Side effects of medications for opioid use disorder (MOUD) such as weight gain contribute to their stigma. Substantial evidence suggests that women have a more severe side effect profile to MOUD than men, and concerns about weight gain during treatment are prevalent. However, the few studies reporting sex differences in weight gain during treatment show conflicting results and are restricted to methadone. In addition, little is known about possible sex differences in weight gain to buprenorphine, which is the most commonly prescribed MOUD in the United States.Methods: To address these issues, we performed a systematic review and meta-analysis on the few studies reporting longitudinal data on sex differences in body mass index (BMI) gain during methadone treatment (Study 1). In a separate study, we also re-analyzed data from trial CTN-0030 of the National Institute on Drug Abuse Clinical Trial Network (NIDA CTN), which involved a 12-week buprenorphine treatment regimen (Study 2; n = 360; 209 Male, 151 Female).Results: For Study 1, across all papers reporting longitudinal data (k = 4, n = 362 OUD patients), there were BMI increases that ranged from 2.2 to 5.4 BMI after at least one year of methadone treatment, but there were no significant sex differences in BMI increases (Standardized Mean Difference, Female > Male = 0.352, SE =0.270; 95 % CI = [-0.18 0.88]; p = .193). Study 2 showed no significant differences in weight before and after 12 weeks of buprenorphine treatment nor did it show sex differences in weight change with treatment (β = 2.34, p = .511).Conclusion: These analyses corroborate evidence of weight gain with methadone treatment but did not observe a sex-based disparity in weight gain with methadone or buprenorphine treatment for OUD. [ABSTRACT FROM AUTHOR]

Summary: Background: The association between body mass index (BMI) and adiposity differs by race/ethnicity. Objective: To examine differences in adiposity by race/Hispanic origin among US youth and explore how those differences relate to differences in BMI using the most recent national data, including non‐Hispanic Asian youth. Methods: Weight, height and DXA‐derived fat mass index (FMI) and percentage body fat (%BF) from 6923 youth 8–19 years in the National Health and Nutrition Examination Survey (NHANES) 2011–2018 were examined. Age‐adjusted mean BMI, FMI and %BF were reported. Sex‐specific linear regression models predicting %BF and FMI were adjusted for age, BMI category and BMI category*race/Hispanic origin interaction. Results: %BF was highest among Hispanic males (28.2%) and females (35.7%). %BF was lower among non‐Hispanic Black (23.9%) compared with non‐Hispanic White (26.0%) and non‐Hispanic Asian (26.6%) males. There was no difference between non‐Hispanic Black females (32.7%) and non‐Hispanic White (33.2%) or non‐Hispanic Asian (32.7%) females. FMI was higher among Hispanic youth compared with non‐Hispanic White youth. Among youth with underweight/healthy weight, predicted %BF and FMI were lower among non‐Hispanic Black males (−2.8%; −0.5) and females (−2.0%; −0.3), compared with non‐Hispanic White youth, and higher among Hispanic males (0.9%; 0.2) and females (2.0%; 0.5), while %BF but not FMI was higher among non‐Hispanic Asian males (1.3%) and females (1.4%). Among females with obesity, non‐Hispanic Asian females had lower %BF (−2.3%) and FMI (−1.7) than non‐Hispanic White females. Conclusions: Differences in %BF and FMI by race/Hispanic origin were not consistent by BMI category among US youth in 2011–2018. [ABSTRACT FROM AUTHOR]

Summary: Objective: Rank the importance of potentially modifiable psychosocial, dietary and environmental risk and protective factors for female adolescent obesity in order to target and inform public health prevention efforts. Utilizing the largest dataset available that captures the onset of the adolescent obesity surge in the USA, the study provides a more robust understanding of paediatric obesity risk factors. Methods: Data were obtained from an observational, longitudinal study conducted between 1989 and 2001, the NHLBI Growth and Health Study. This study includes girls aged 9–19 years from three urban US locations, with Black and White girls generally represented equally. Data were analysed using multiple regression, random forest and propensity score matching to determine the strongest adiposity risk and protective factors during ages 9–12 predicting adiposity at age 19 with multiple methods to maximize the ability to identify possible public health interventions. Multiple linear regression and random forest analysis identified the strongest associations among 288 risk and protective factors selected from the study's literature review. For the 190 factors associated with follow‐up adiposity from the data, propensity score matching was used to control for confounding of these factors. Results: Findings suggest that highest priority interventional targets across the domains surveyed are lowering specific nutrients; eating meals with others or during activities without skipping; parents fixing evening snacks; improving perceptions of non‐extremes as the healthy weight; improving self‐worth, physical activity and social competence; and limiting any negative impact of dieting relatives. Similar associations were observed for Black and White girls. Conclusion: The clinical implications of these findings allow health practitioners to target behavioural change efforts and address social and environmental factors that have demonstrated higher prioritization value for early obesity interventional efforts for adolescents. [ABSTRACT FROM AUTHOR]